1. Field of the Invention
The present invention relates to a method of processing information in artificial neural networks, or of executing high-speed arithmetic processing among the artificial neurons of artificial neural networks.
2. Description of the Related Art
Recently, attempts have been made to constitute an artificial neural network by coupling a plurality of artificial neurons by means of links, and to use the artificial neural network in order to solve combination of optimizing problems or perform pattern recognition. The artificial neural network can process a great volume of information, but at rather a low speed. A strong demand has arisen for a method of processing information in the artificial neural networks at a sufficiently high speed.
Generally, a large number of operations such as additions and multiplications are performed in an artificial neural network of this type. A Hopfield model, i.e., a typical artificial neural network is disclosed in J. J. Hopfield, Neural Networks Physical System with Emergent Collective Computation Abilities, Proceedings of the National Academy of Sciences Vol.79, pp. 2554-2558, 1982, and J. J. Hopfield, Neurons with Graded Response Have Collective Computational Properties like Those of Two-State Neurons, Proceedings of the National Academy of Sciences, Vol. 81, pp. 3088-3092, 1984. In the Hopfield model, each of the artificial neurons obtains the output values by all other neurons coupled to it by means of links, and generates and supplies a value to the other neurons through the link.
The output value Oj of the artificial neuron j is given: ##EQU1## where n is the number of all artificial neurons used, Oi is the output value of neuron i, g is a monotone increasing function and Wji is the weight coefficient of the link which connects artificial neurons i with j.
Therefore, to calculate an output value of an artificial neuron, many arithmetic operations, specified below, need to be performed:
______________________________________ Multiplication n times Addition n - 1 times Function processing n times ______________________________________
Thus, in order to calculate an output value for each artificial neuron, it is necessary to carry out so great an amount of computation as follows:
______________________________________ Multiplication n.sup.2 times Addition n.sup.2 - n times Function processing n times ______________________________________
As has been described, attempts have hitherto been made to use artificial neural networks in order to analyze optimizing problems and the like. The amount of information which an artificial neural network needs to process to analyze these problems is enormously large, and much time is required to perform arithmetic operations by means of the neural network.